Download The idea of cognitive energy preservation comes across quite

The idea of cognitive energy preservation comes across quite intuitively. Humans tend to
do what requires the least of them, if given the opportunity. The well-known idiom “the path of
least resistance” came about due to this natural desire to take the easy route. However, when
added variables such as rewards, level of effort, and decision making come into play, it is
preferable to know the parameters of cognitive energy preservation.
Early Greek philosophers suggested that much of human behavior can be similar to
animal behavior; one behavior being the desire to seek pleasure and to avoid pain (Hergenhan &
Henley, 2014). This paradigm is still popular among psychologists today. Physical actions such
as moving and navigating between objects or mental strains such as solving puzzles, being
attentive, or rotating objects in one’s mind can greatly exhaust our energy (Morsella, Feinberg,
Cigarchi, Newton, Williams, 2011). Decision making can also be a strenuous task for the mind.
Conflict in a decision-making process causes avoidance learning, prompting the decision-maker
to bias themselves toward more efficient and simple forms of information processing to avoid
cognitive failure (Botnivik, 2007). Our interaction with the environment requires us to make
numerous decisions every day. Botvinick (2007) and Hull (1943) have hypothesized that our
behaviors of avoiding situations associated with intense effort is a reflex in which our bodies are
automatically inclined to associate negative responses to highly demanding situations.
People have been shown to approach tasks in a mental cost-benefit analysis. Hull’s law of less
work states, if given two tasks, a person who does the more difficult task will gradually start
choosing the task that requires the least amount of effort. Although Hull’s theory was about the
demands of physical work, he thought that we should be able to apply this principle to the effort
people put into their cognitive demands. The theory is that people like to spend as little mental
energy as possible in their decision making process (Hull, 1943). This assumption was better
solidified by Kool et al (2010). Kool and colleagues have continued studying the topic of
avoidance of cognitive demand since publishing their 2010 manuscript on the subject. Since
then, the team has found a sample balance of the labor/leisure tradeoff and what contributes to
the tradeoff. Costs that affect the tradeoff include the effort that we put into tasks and making
decisions between tasks (Hockey, 2011). By default, our minds prefer cognitive leisure; as
varying goals are acquired, we learn to forego the default desire in place for something profitable
(Kool, 2012). For us it seems we will attempt to do so almost exclusively as cognitive misers.
Neuroscience corroborated the idea when Salamone and colleagues studied variations in
rats’ brains in order to observe the role of dopamine in determining the response cost of decisionmaking. They found that interfering with dopamine transmission had a strong influence over
effort-related choice behaviors. When dopamine was depleted, the rats would change their
behavior from choosing food-reinforced tasks with high cognitive demand to choosing tasks with
low cognitive demand but little reinforcement (Salamone, Correa, Nunes, Randall, and Pardo,
2012). As a result of similar studies, people have thought that cognitive capacity can be measure
as a finite tank of resources. As research shows, cognitive failure does not only stem from a lack
of resources such as glucose to the brain or from a “biological tank”, but instead our willpower
can add to our cognitive capacity (Hockey, 2011). Hence, with lack of nutrition to the brain and
lack of willpower comes cognitive fatigue in the face of cognitively demanding work.
The original work of Kool and colleagues shows the desire to avoid such fatigue,
however a replication with a larger sample size would greatly serve the authentication of their
findings. Our aim is to fulfill said need and further account for an untested variable. Relative to
the findings and theoretical stances that base the hypotheses of Kool and his colleagues, there is
another explanation that could account for individual differences of cognitive demand and
decision making. The phenomenon is contributed to a personality trait identified as the need for
cognitive demand (Cacioppo, Petty, Feinstein, Blair, & Jarvis, 1996) or learned industriousness
(Eisenberger, 1992). A brief explanation of the phenomena is as follows: across different
circumstances certain individuals are more inclined to think deeply about issues compared to
others. Individuals high in the need for cognition tend to analyze and think critically while
enjoying the problem solving process (Cacioppo & Petty, 1982).
In the article, it was conceded that, as a general principle, such concepts do seem
contrary to demand avoidance, but the following statement was made to refute the need to test
for such a phenomenon: “Selection of high-effort courses of action need not contradict the
proposition that effort weighs negatively in the underlying tradeoff. The crossword-puzzle player
is like a weight-lifter: Both are subject to the law of least (physical or mental) effort, but effortrelated costs may be countered by other incentives.” (Kool, McGuire, Rosen, & Botvinick 2010)
The question still remains, however, if any significant factor can be measured and identified
within participants’ behavior outside of that hypothesized by Kool and colleagues to explain
mixed results. If variations are present within the data that suggest individual variation of
conformity to the principle of demand avoidance, it could be possible that the variable of
personality is weighing in more than previously considered. It is upon that potentiality that
justification can be founded to test for the need for cognition. Setting aside that basic curiosity
that might drive such an endeavor, it is also scientifically mindful to entertain such a falsifiable
explanation for deviation of participants from demand avoidance. If incentives are enough to
mitigate the significant personality factor of need for cognition and it too yields to the principle
of least effort, then the data & its interpretation will surely indicate accordingly. In light of this,
we hypothesize that a low proportion of low-demand preference will show correlation with those
that rate high on the Need for Cognition Scale. We also desire to verify the hypothesis of Kool
et. al., hopefully showing a larger preference for low-demand tasks.